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Heterogeneous data integration: Challenges and opportunities.

I Made Putrama1,2, Péter Martinek1

  • 1Department of Electronics Technology, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Budapest, Hungary.

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|September 17, 2024
PubMed
Summary

Virtual data integration offers a cost-effective alternative to physical systems for handling dynamic market needs. Research highlights a focus on big data, semantic challenges, and the need to address unstructured data integration.

Keywords:
Big dataData sourcesHeterogeneousIntegrationOntologyReview

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Area of Science:

  • Computer Science
  • Data Management
  • Information Systems

Background:

  • Organizations require robust data integration to adapt to dynamic markets.
  • Physical data integration systems are costly to implement and maintain.
  • Virtual data integration emerges as a cost-effective, research-intensive alternative in the big data era.

Purpose of the Study:

  • To provide a comprehensive overview of heterogeneous data integration research.
  • To focus on methodologies and approaches for integrating diverse data sources.
  • To identify key trends, challenges, and future research directions in data integration.

Main Methods:

  • Systematic survey of existing publications on heterogeneous data integration.
  • Analysis of research trends across various domains, with a focus on big data.
  • Identification of prevalent challenges, particularly semantic integration and unstructured data.

Main Results:

  • Research is widespread but often domain-agnostic, prioritizing big data over specific applications.
  • Semantic challenges represent a primary focus for researchers in data integration.
  • Significant gaps exist in addressing integration issues related to semantics and unstructured data formats.

Conclusions:

  • Further investigation is needed into integrating semantics and unstructured data.
  • The intersection of machine learning, data integration, and privacy presents a promising research avenue.
  • Case studies can offer valuable insights into broader data integration challenges.